Next Article in Journal
The Interaction between Genetic Polymorphisms in FTO and TCF7L2 Genes and Dietary Intake with Regard to Body Mass and Composition: An Exploratory Study
Previous Article in Journal
Understanding Implementation Challenges to Genetic Testing for Familial Hypercholesterolemia in the United States
Article Menu

Export Article

Open AccessArticle
J. Pers. Med. 2019, 9(1), 10; https://doi.org/10.3390/jpm9010010

VARIFI—Web-Based Automatic Variant Identification, Filtering and Annotation of Amplicon Sequencing Data

1
Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, Dr. Bohrgasse 9, 1030 Vienna, Austria
2
Department of Applied Genetics und Cell Biology, University of Natural Resources and Life Sciences, Muthgasse 18, 1190 Vienna, Austria
3
Institute of Pathology, Medical University Vienna, Währinger Gürtel 18-20, 1090 Vienna, Austria
4
Bioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna, 1090 Vienna, Austria
*
Author to whom correspondence should be addressed.
Received: 28 December 2018 / Revised: 26 January 2019 / Accepted: 28 January 2019 / Published: 1 February 2019
Full-Text   |   PDF [434 KB, uploaded 14 March 2019]   |  

Abstract

Fast and affordable benchtop sequencers are becoming more important in improving personalized medical treatment. Still, distinguishing genetic variants between healthy and diseased individuals from sequencing errors remains a challenge. Here we present VARIFI, a pipeline for finding reliable genetic variants (single nucleotide polymorphisms (SNPs) and insertions and deletions (indels)). We optimized parameters in VARIFI by analyzing more than 170 amplicon-sequenced cancer samples produced on the Personal Genome Machine (PGM). In contrast to existing pipelines, VARIFI combines different analysis methods and, based on their concordance, assigns a confidence score to each identified variant. Furthermore, VARIFI applies variant filters for biases associated with the sequencing technologies (e.g., incorrectly identified homopolymer-associated indels with Ion Torrent). VARIFI automatically extracts variant information from publicly available databases and incorporates methods for variant effect prediction. VARIFI requires little computational experience and no in-house compute power since the analyses are conducted on our server. VARIFI is a web-based tool available at varifi.cibiv.univie.ac.at. View Full-Text
Keywords: personalized medicine; cancer; amplicon sequencing; variant finding; pipeline personalized medicine; cancer; amplicon sequencing; variant finding; pipeline
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Supplementary material

SciFeed

Share & Cite This Article

MDPI and ACS Style

Krunic, M.; Venhuizen, P.; Müllauer, L.; Kaserer, B.; von Haeseler, A. VARIFI—Web-Based Automatic Variant Identification, Filtering and Annotation of Amplicon Sequencing Data. J. Pers. Med. 2019, 9, 10.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
J. Pers. Med. EISSN 2075-4426 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top